Cai Huajun, Zeng Jintao, Wang Ye, Zhuang Jinfu, Liu Xing, Guan Guoxian
Department of Colorectal Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Front Immunol. 2024 Dec 20;15:1472620. doi: 10.3389/fimmu.2024.1472620. eCollection 2024.
This study aimed to investigate the prognostic significance of the log odds of negative lymph nodes/T stage ratio (LONT) and develop an efficient prognostic staging system using LONT in patients with colon mucinous adenocarcinoma (MAC).
This study included 5,236 patients diagnosed with colon MAC obtained from the Surveillance, Epidemiology, and End Results database. The Kaplan-Meier method, subgroup analysis, receiver operating characteristic (ROC) curve, and Cox proportional hazard regression model were used to determine the clinical outcomes. Recursive partitioning analysis (RPA) was used to develop a novel prognostic system.
The 1-, 3-, and 5-year ROC curves, used to predict cancer-specific survival (CSS) and overall survival (OS), demonstrated that the areas under the ROC curve for LONT were superior to those of pT, pN, and pTNM stages. Additionally, a lower LONT was correlated with worse clinical outcomes. The LONT classification efficiently differentiated the prognosis of patients in terms of OS and CSS. Multivariate Cox analyses revealed that LONT was an independent prognostic factor for both CSS and OS. Based on the pT stage and LONT, a novel prognostic staging system was developed using RPA, demonstrating a good prognostic predictive performance.
A lower LONT was associated with worse survival in patients with colon MAC. The pT stage and LONT-based prognostic staging system facilitated risk stratification in these patients.
本研究旨在探讨阴性淋巴结对数/T分期比值（LONT）的预后意义，并开发一种使用LONT的高效预后分期系统，用于结肠黏液腺癌（MAC）患者。
本研究纳入了5236例从监测、流行病学和最终结果数据库中获取的诊断为结肠MAC的患者。采用Kaplan-Meier法、亚组分析、受试者工作特征（ROC）曲线和Cox比例风险回归模型来确定临床结局。采用递归划分分析（RPA）开发一种新的预后系统。
用于预测癌症特异性生存（CSS）和总生存（OS）的1年、3年和5年ROC曲线显示，LONT的ROC曲线下面积优于pT、pN和pTNM分期。此外，较低的LONT与较差的临床结局相关。LONT分类在OS和CSS方面有效地分化了患者的预后。多变量Cox分析显示，LONT是CSS和OS的独立预后因素。基于pT分期和LONT，使用RPA开发了一种新的预后分期系统，显示出良好的预后预测性能。
较低的LONT与结肠MAC患者较差的生存相关。基于pT分期和LONT的预后分期系统有助于对这些患者进行风险分层。
